scholarly journals PARAFOG v2.0: a near real-time decision tool to support nowcasting fog formation events at local scales

2021 ◽  
Author(s):  
Jean-François Ribaud ◽  
Martial Haeffelin ◽  
Jean-Charles Dupont ◽  
Marc-Antoine Drouin ◽  
Felipe Toledo ◽  
...  

Abstract. An improved version of the near-real time decision tool PARAFOG (PFG2) is presented to retrieve pre-fog alert levels and to discriminate between radiation (RAD) and stratus lowering (STL) fog situations. PFG2 has two distinct modules to monitor the physical processes involved in RAD and STL fog formation and is evaluated at European sites. The modules are based on innovative fuzzy logic algorithms to retrieve fog alert levels (low, moderate, high) specific to RAD/STL conditions, minutes to hours prior to fog onset. The PFG2-RAD module assesses also the thickness of the fog. Both the PFG2-RAD and PFG2-STL modules rely on the combination of visibility observations and automatic lidar and ceilometer (ALC) measurements. The overall performance of the PFG2-RAD and -STL modules is evaluated based on 9 years of measurements at the SIRTA observatory near Paris and up to two fog seasons at the Paris-Roissy, Vienna, Munich and Zurich airports. At all sites, pre-fog alert levels retrieved by PFG2 are found to be consistent with the local weather analysis. The advanced PFG2 algorithm performs with a hit rate of about 100 % for both considered fog types, and presents a false alarm ratio on the order of 10 % (30 %) for RAD (STL) fog situations. Finally, the first high alerts that result in a subsequent fog event are found to occur for periods of time ranging from −120 minutes to fog onset, with first high alerts occurring earlier for RAD than STL cases.

2021 ◽  
Vol 14 (12) ◽  
pp. 7893-7907
Author(s):  
Jean-François Ribaud ◽  
Martial Haeffelin ◽  
Jean-Charles Dupont ◽  
Marc-Antoine Drouin ◽  
Felipe Toledo ◽  
...  

Abstract. An improved version of the near-real-time decision tool PARAFOG (PFG2) is presented to retrieve pre-fog alert levels and to discriminate between radiation (RAD) and stratus lowering (STL) fog situations. PFG2 has two distinct modules to monitor the physical processes involved in RAD and STL fog formation and is evaluated at European sites. The modules are based on innovative fuzzy logic algorithms to retrieve fog alert levels (low, moderate, high) specific to RAD/STL conditions, minutes to hours prior to fog onset. The PFG2-RAD module assesses also the thickness of the fog. Both the PFG2-RAD and PFG2-STL modules rely on the combination of visibility observations and automatic lidar and ceilometer (ALC) measurements. The overall performance of the PFG2-RAD and PFG2-STL modules is evaluated based on 9 years of measurements at the SIRTA (Instrumented Site for Atmospheric Remote Sensing Research) observatory near Paris and up to two fog seasons at the Paris-Roissy, Vienna, Munich, and Zurich airports. At all sites, pre-fog alert levels retrieved by PFG2 are found to be consistent with the local weather analysis. The advanced PFG2 algorithm performs with a hit rate of about 100 % for both considered fog types and presents a false alarm ratio on the order of 10 % (30 %) for RAD (STL) fog situations. Finally, the first high alerts that result in a subsequent fog event are found to occur for periods of time ranging from −120 min to fog onset, with the first high alerts occurring earlier for RAD than STL cases.


2020 ◽  
Vol 14 (1) ◽  
pp. 113-119
Author(s):  
Zhang Su

Background: In recent years, sudden deaths of primary and secondary school students caused by sports activities have drawn great attention in education and medical circles. It is necessary for schools to monitor the physical condition of the students in order to reasonably set the duration of their physical activity. At present, the physical condition monitoring instruments used in various hospitals are expensive, bulky, and difficult to operate, and the detection process is complicated. Therefore, existing approaches cannot meet the needs of physical education teachers on campus for detecting the physical condition of students. Methods: This study designs a portable human-physiological-state monitoring and analysis system. Real-time communication between a wearable measurement device and a monitoring device can be ensured by real-time detection of the environment and power control of the transmitted signal. Results: From a theoretical point of view, the larger the number of segments M, the more significantly the reduction of false alarm probability. The simulation results also show this fact. Compared with the conventional early warning mechanism, the probability of a false alarm for the proposed system is lower, and the greater the number of segments, the faster its reaction speed. Conclusion: The portable monitoring system of student physical condition for use in physical education of primary and middle school students proposed in this paper ensures real-time monitoring of the members within the system in an open environment, and further proposes an early warning mechanism for combining multiple vital sign parameters. In addition, the proposed system functions faster; the average early warning time required is only one-quarter of that of the conventional system.


Author(s):  
Cyrus K. Foroughi ◽  
Shannon Devlin ◽  
Richard Pak ◽  
Noelle L. Brown ◽  
Ciara Sibley ◽  
...  

Objective Assess performance, trust, and visual attention during the monitoring of a near-perfect automated system. Background Research rarely attempts to assess performance, trust, and visual attention in near-perfect automated systems even though they will be relied on in high-stakes environments. Methods Seventy-three participants completed a 40-min supervisory control task where they monitored three search feeds. All search feeds were 100% reliable with the exception of two automation failures: one miss and one false alarm. Eye-tracking and subjective trust data were collected. Results Thirty-four percent of participants correctly identified the automation miss, and 67% correctly identified the automation false alarm. Subjective trust increased when participants did not detect the automation failures and decreased when they did. Participants who detected the false alarm had a more complex scan pattern in the 2 min centered around the automation failure compared with those who did not. Additionally, those who detected the failures had longer dwell times in and transitioned to the center sensor feed significantly more often. Conclusion Not only does this work highlight the limitations of the human when monitoring near-perfect automated systems, it begins to quantify the subjective experience and attentional cost of the human. It further emphasizes the need to (1) reevaluate the role of the operator in future high-stakes environments and (2) understand the human on an individual level and actively design for the given individual when working with near-perfect automated systems. Application Multiple operator-level measures should be collected in real-time in order to monitor an operator’s state and leverage real-time, individualized assistance.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Arpit Jain ◽  
Abhinav Sharma ◽  
Vibhu Jately ◽  
Brian Azzopardi ◽  
Sushabhan Choudhury

Author(s):  
Chun-ying Huang ◽  
Yun-chen Cheng ◽  
Guan-zhang Huang ◽  
Ching-ling Fan ◽  
Cheng-hsin Hsu

Real-time screen-sharing provides users with ubiquitous access to remote applications, such as computer games, movie players, and desktop applications (apps), anywhere and anytime. In this article, we study the performance of different screen-sharing technologies, which can be classified into native and clientless ones. The native ones dictate that users install special-purpose software, while the clientless ones directly run in web browsers. In particular, we conduct extensive experiments in three steps. First, we identify a suite of the most representative native and clientless screen-sharing technologies. Second, we propose a systematic measurement methodology for comparing screen-sharing technologies under diverse and dynamic network conditions using different performance metrics. Last, we conduct extensive experiments and perform in-depth analysis to quantify the performance gap between clientless and native screen-sharing technologies. We found that our WebRTC-based implementation achieves the best overall performance. More precisely, it consumes a maximum of 3 Mbps bandwidth while reaching a high decoding ratio and delivering good video quality. Moreover, it leads to a steadily high decoding ratio and video quality under dynamic network conditions. By presenting the very first rigorous comparisons of the native and clientless screen-sharing technologies, this article will stimulate more exciting studies on the emerging clientless screen-sharing technologies.


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